CRM - November 2007 - (Page 46) SECRET OF MY SUCCESS Policing Better Data A U.K. police department relies on Informatica to handcuff dirty data Graham Dawson, HEAD OF INFORMATION SERVICES FOR THE HUMBERSIDE POLICE AUTHORITY | as told to Colin Beasty ■ Tell us about your organization. Humberside Police is one of 43 police departments in England and Wales, and is responsible for policing a sizable county in northeast England. All told, our department consists of approximately 4,000 police officers and related personnel. ■ What problems were you facing? We had a number of challenges, many of which a typical organization or business wouldn’t encounter. For example, while a customer will rarely provide a business with fake contact information, a [criminal] suspect does this all the time. This presents some unique challenges. Additionally, we collect data from numerous outside sources, including other local and U.K.-based law-enforcement agencies, such as Scotland Yard. So in the end, we had this heterogeneous collection of suspect and criminal data that was coming in and being entered into disparate systems. We had a central database to record criminal events as they occurred, but it was separate from many of the other databases. To make a long story short, it was hampering our ability to provide our officers with timely and accurate information, reducing the efficiency of our intelligence unit, and hindering our ability to operate with other law-enforcement agencies. ■ Why did you select Informatica? In the autumn of 2005, we realized we needed a tool to cleanse and match the data coming in from the disparate systems into a central data warehouse. We did a proof-of-concept and tested several data-cleansing products. We were shopping for a product that would show us where the information was [questionable], and help us pick out areas that needed to be corrected—so this was very much a data-governance issue. In the end, we were most impressed with Informatica from both price and functionality standpoints. ■ How did the implementation proceed? We ran into numerous technical glitches associated with a data-quality project, such as determining data distribution and integration 46 CUSTOMER RELATIONSHIP MANAGEMENT | NOVEMBER 2007 woes, but all in all, it went off like clockwork. Our internal databases were built using Microsoft SQL Server, with an Autonomy search engine running on top of it. We use Informatica to cleanse information as it’s coming into the data warehouse, info such as names, contact information, addresses, records—all that good stuff. Then, the Autonomy search engine distributes that cleansed info out to our police officers. To ensure end-user buy-in, we involved the officers and our intelligence unit from the very beginning and gave them demonstrations on how the new system would work. We also worked closely with our intelligence unit to determine which data is leveraged the most and to map data-governance and -stewardship issues. ■ What have been the main rewards? Since implementing Informatica, the Humberside Police department has seen the accuracy of its vehicleregistration numbers climb from 83 percent to 98 percent, and that’s just one form of data that’s seen a big improvement in accuracy. Our intelligence unit has been able to analyze data like never before, and it’s given us the ability to verify case leads with lawenforcement agencies throughout the country. There are hundreds of specific examples. Oftentimes, information is collected under duress or pressure, and that can lead to inaccurate data. We’re now using Informatica to cleanse that information and match it up with complete records to give our officers the most up-to-date information. 5 FAST FACTS >> AGE OF THE INITIATIVE? 1 1⁄2 years >> WHO WAS INVOLVED? Myself, our IT managers, and the department head of our intelligence unit >> BEST IDEA? Coming up with a separate data force to oversee all of the data governance issues >> BIGGEST SURPRISE? The inaccuracy of the data when we started the implementation >> BIGGEST CRM MISTAKE MADE? Failing to understand the impact dirty data can have on an IT implementation www.destinationCRM.com http://www.destinationCRM.com
Table of Contents Feed for the Digital Edition of CRM - November 2007 CRM - November 2007 Contents Front Office Reality Check Customer Centricity Have You Caught It? The Mother of Enterprise Information Market Focus: Technology: The Simple Truth about Complex Manufacturing Q&A: Gianforte Talks CRM Required Reading Predicting Profitability Checking the Pulse of the Contact Center Cast a Narrow Net Modern Times, Modern Methods Primos Hunting Calls Snares Efficiency Nailing It Down Moving in on Mortgage Delinquencies RDS Delivery Delivers on Service Secret of My Success Re:Tooling The Tipping Point Pint of View CRM - November 2007 CRM - November 2007 - CRM - November 2007 (Page Cover1) CRM - November 2007 - CRM - November 2007 (Page Cover2) CRM - November 2007 - Contents (Page 3) CRM - November 2007 - Contents (Page 4) CRM - November 2007 - Contents (Page 5) CRM - November 2007 - Front Office (Page 6) CRM - November 2007 - Front Office (Page 7) CRM - November 2007 - Reality Check (Page 8) CRM - November 2007 - Reality Check (Page 9) CRM - November 2007 - Customer Centricity (Page 10) CRM - November 2007 - Customer Centricity (Page 11) CRM - November 2007 - Have You Caught It? (Page 12) CRM - November 2007 - The Mother of Enterprise Information (Page 13) CRM - November 2007 - Market Focus: Technology: The Simple Truth about Complex Manufacturing (Page 14) CRM - November 2007 - Market Focus: Technology: The Simple Truth about Complex Manufacturing (Page 15) CRM - November 2007 - Q&A: Gianforte Talks CRM (Page 16) CRM - November 2007 - Required Reading (Page 17) CRM - November 2007 - Predicting Profitability (Page 18) CRM - November 2007 - Predicting Profitability (Page 19) CRM - November 2007 - Predicting Profitability (Page 20) CRM - November 2007 - Predicting Profitability (Page 21) CRM - November 2007 - Predicting Profitability (Page 22) CRM - November 2007 - Predicting Profitability (Page S1) CRM - November 2007 - Predicting Profitability (Page S2) CRM - November 2007 - Predicting Profitability (Page S3) CRM - November 2007 - Predicting Profitability (Page S4) CRM - November 2007 - Predicting Profitability (Page S5) CRM - November 2007 - Predicting Profitability (Page S6) CRM - November 2007 - Predicting Profitability (Page S7) CRM - November 2007 - Predicting Profitability (Page S8) CRM - November 2007 - Predicting Profitability (Page 23) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 24) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 25) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 26) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 27) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 28) CRM - November 2007 - Checking the Pulse of the Contact Center (Page 29) CRM - November 2007 - Cast a Narrow Net (Page 30) CRM - November 2007 - Cast a Narrow Net (Page 31) CRM - November 2007 - Cast a Narrow Net (Page 32) CRM - November 2007 - Cast a Narrow Net (Page 33) CRM - November 2007 - Cast a Narrow Net (Page 34) CRM - November 2007 - Cast a Narrow Net (Page 35) CRM - November 2007 - Modern Times, Modern Methods (Page 36) CRM - November 2007 - Modern Times, Modern Methods (Page 37) CRM - November 2007 - Modern Times, Modern Methods (Page 38) CRM - November 2007 - Modern Times, Modern Methods (Page 39) CRM - November 2007 - Modern Times, Modern Methods (Page 40) CRM - November 2007 - Modern Times, Modern Methods (Page 41) CRM - November 2007 - Modern Times, Modern Methods (Page 42) CRM - November 2007 - Nailing It Down (Page 43) CRM - November 2007 - Moving in on Mortgage Delinquencies (Page 44) CRM - November 2007 - RDS Delivery Delivers on Service (Page 45) CRM - November 2007 - Secret of My Success (Page 46) CRM - November 2007 - Re:Tooling (Page 47) CRM - November 2007 - The Tipping Point (Page 48) CRM - November 2007 - The Tipping Point (Page 49) CRM - November 2007 - Pint of View (Page 50) CRM - November 2007 - Pint of View (Page Cover3) CRM - November 2007 - Pint of View (Page Cover4)
For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.